MétaCan
Menu
Back to cohort
Record W2073065225 · doi:10.1159/000315076

Regulation of Human Cardiac Ion Channel Genes by MicroRNAs: Theoretical Perspective and Pathophysiological Implications

2010· article· en· W2073065225 on OpenAlexaff
Xiaobin Luo, Haijun Zhang, Jiening Xiao, Zhiguo Wang

Bibliographic record

VenueCellular Physiology and Biochemistry · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsmicroRNAIon channelIn silicoComputational biologyBiologyBioinformaticsGene expressionGeneRegulation of gene expressionCell biologyGeneticsReceptor

Abstract

fetched live from OpenAlex

Excitability is a fundamental characteristic of cardiac cells, which is delicately determined by ion channel activities modulated by many factors. MicroRNA (miRNA) expression is dynamically regulated and altered miRNA expression can render expression deregulation of ion channel genes leading to channelopathies-arrhythmogenesis. Indeed, evidence has emerged indicating the crucial role of miRNAs in controlling cardiac excitability by regulating expression of ion channel genes at the post-transcriptional level. However, the very limited experimental data in the literature hinder our understanding of the role of miRNAs and the often one-to-one interaction between miRNA and ion-channel gene in the published studies also casts a doubt about fullness of our view. Unfortunately, currently available techniques do not permit thorough characterization of miRNA targeting; computational prediction programs remain the only source for rapid identification of a putative miRNA target in silico. We conducted a rationally designed bioinformatics analysis in conjunction with experimental approaches to identify the miRNAs from the currently available miRNA databases which have the potential to regulate human cardiac ion channel genes and to validate the analysis with several pathological settings associated with the deregulated miRNAs and ion channel genes in the heart. We established a matrix of miRNAs that are expressed in cardiac cells and have the potential to regulate the genes encoding cardiac ion channels and transporters. We were able to explain a particular ionic remodeling process in hypertrophy/heart failure, myocardial ischemia, or atrial fibrillation with the corresponding deregulated miRNAs under that pathological condition; the changes of miRNAs appear to have anti-correlation with the changes of many of the genes encoding cardiac ion channels under these situations. These results indicate that multiple miRNAs might be critically involved in the electrical/ionic remodeling processes of cardiac diseases through altering their expression in cardiac cells, which has not been uncovered by previous experimental studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.224
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations95
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCellular Physiology and BiochemistrySame topicMicroRNA in disease regulationFrench-language works237,207